In order to study the controllability of brain networks efficiently, we gave a directionality to the connectomes.
Despite the fact that it is not currently possible for neuroimaging techniques to discern the directionality of bundles of axons, it is known that each neuron propagates signals through a well-defined direction from the soma to the axon terminal.
Previous efforts to direct a connectome relied on the hypothesis that, given a set of brain networks, edges present for all subjects are the oldest, and any new edge would be directed from the new node to the existing cluster [1]}.
However, a limitation of this method is that it is strictly dependent on the initial set of networks, and the procedure would not be easily scalable.
Other methods based on local navigation and communicability were devised to infer the directionality of neural signaling, but since they operate best for nodes connected by longer paths, they are not well-suited to perform inference for structurally connected nodes [2]}.
Our approach was instead inspired by the diffusion processes taking place in the connectome [3]}, [4]}, [5]}, [6]}, [7]} and preserves the hierarchical and modular properties of the anatomical pathways.
